Yilema Seyifemickael Amare, Shiferaw Yegnanew A, Nakhaeirad Najmeh, Chen Ding-Geng
Department of Statistics, College of Natural and Computational Science, Debre Tabor University, Debre Tabor, Ethiopia.
Department of Statistics, University of Pretoria, Pretoria, South Africa.
Front Pediatr. 2025 Aug 21;13:1559140. doi: 10.3389/fped.2025.1559140. eCollection 2025.
Globally, anemia poses a serious health challenge for children under the age of five, and Ethiopia is one of the countries significantly affected by this issue. The 2016 Ethiopian Demographic and Health Survey (DHS) data sets were employed to evaluate anemia risk among children aged 6-59 months. Due to limited research has been conducted on childhood anemia spatial disparities at the Ethiopian zonal level, and it is essential for developing zonal-level interventions for inform policy recommendations.
This study was examined the geospatial disparities in anemia prevalence among children aged 6-59 months. We used a semi-parametric additive model with spatial smoothing to assess zone-level variation in anemia risk while adjusting for key covariates. Each predictor variable was spatially adjusted using non-parametric smoothing techniques based on geolocation parameters, and corresponding maps for each predictor.
A regularized random forest techniques was employed to identify the most influential predictors of childhood anemia and enhance the model predictive performance. Our findings revealed that the regional states of Somalia, Afar, and Dire Dawa exhibit the highest risk levels for childhood anemia. Furthermore, the risk of anemia in children varies spatially across different zones in Ethiopia. The most prominent hotspots for childhood anemia were in the country's Northeastern, Eastern, and Southeastern regions. In contrast, the areas with the lowest risk were in Northwestern, Western, and Southwestern zones of Ethiopia.
The significant spatial disparities in anemia risk across the administrative zones of Ethiopia, indicating that the distribution of each predictor variable is not uniform. These findings provide valuable insights for policymakers, enabling the development of geographically targeted interventions to mitigate anemia risk at the zonal level.
在全球范围内，贫血对五岁以下儿童构成了严峻的健康挑战，埃塞俄比亚是受这一问题严重影响的国家之一。2016年埃塞俄比亚人口与健康调查（DHS）数据集被用于评估6至59个月大儿童的贫血风险。由于在埃塞俄比亚区域层面上针对儿童贫血空间差异的研究有限，因此制定区域层面的干预措施以提供政策建议至关重要。
本研究考察了6至59个月大儿童贫血患病率的地理空间差异。我们使用了带有空间平滑的半参数加法模型来评估贫血风险的区域层面变化，同时对关键协变量进行调整。每个预测变量都基于地理位置参数使用非参数平滑技术进行空间调整，并为每个预测变量绘制相应的地图。
采用正则化随机森林技术来识别儿童贫血最具影响力的预测因素，并提高模型的预测性能。我们的研究结果显示，索马里、阿法尔和迪雷达瓦等地区儿童贫血风险水平最高。此外，埃塞俄比亚不同区域儿童贫血风险在空间上存在差异。儿童贫血最突出的热点地区位于该国的东北部、东部和东南部地区。相比之下，风险最低的地区位于埃塞俄比亚的西北部、西部和西南部区域。
埃塞俄比亚各行政区贫血风险存在显著的空间差异，这表明每个预测变量的分布并不均匀。这些发现为政策制定者提供了有价值的见解，有助于制定因地制宜的干预措施，以降低区域层面的贫血风险。
